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Efficient energy utilization based on task distribution and cooling airflow management in a data center

机译:基于任务分布和冷却气流管理的高能量利用数据中心

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With the recent emergence of smartphones, cloud computing, and the Internet of Things (IoT), our society has become more dependent on the Internet. In these circumstances, increasing energy consumption in data centers is becoming a crucial problem worldwide and data center managers are required to run them efficiently in terms of energy consumption. This study aims to reduce cooling airflow energy by achieving appropriate task distribution and adding a shutter control system, which reduces the energy consumption of an air-conditioner. In most cases, servers tend to be unnecessarily cooled at low temperatures, even when their exhaust temperatures are not high. Our proposed method solves this problem by using shutter control and introducing a task allocation method. We built an experimental rack model and implemented our proposed control system, validating it with a real HTTP data request. The results show that our experimental system reduces the cooling airflow energy by 4.4%.
机译:随着最近的智能手机,云计算和事物互联网(物联网),我们的社会变得更加依赖互联网。在这些情况下,数据中心的能耗增加正在成为一个至关重要的问题,全球和数据中心管理人员需要在能耗方面有效地运行它们。本研究旨在通过实现适当的任务分布和添加快门控制系统来减少冷却气流能量,这降低了空调的能量消耗。在大多数情况下,即使它们的排气温度不高,也倾向于在低温下不必要地冷却服务器。我们所提出的方法通过使用快门控制并引入任务分配方法来解决这个问题。我们建立了一个实验机架模型并实现了我们提出的控制系统,用真正的HTTP数据请求验证。结果表明,我们的实验系统将冷却气流能量降低4.4%。

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